Towards a Learned Cost Model for Distributed Spatial Join: Data, Code & Models
Towards a Learned Cost Model for Distributed Spatial Join: Data, Code & Models
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面向分布式空间连接的学习成本模型:数据、代码
DOI:
10.1145/3511808.3557712
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发表时间:
2022
期刊:
影响因子:
--
通讯作者:
Eldawy, Ahmed
中科院分区:
文献类型:
--
作者:
Vu, Tin;Belussi, Alberto;Migliorini, Sara;Eldawy, Ahmed
Geospatial data comprise around 60% of all the publicly available data. One of the essential and most complex operations that brings together multiple geospatial datasets is the spatial join operation. Due to its complexity, there is a lot of partitioning techniques and parallel algorithms for the spatial join problem. This leads to a complex query optimization problem: which algorithm to use for a given pair of input datasets that we want to join? With the rise of machine learning, there is a promise in addressing this problem with the use of various learned models. However, one of the concerns is the lack of a standard and publicly available data to train and test on, as well as the lack of accessible baseline models. This resource paper helps the research community to solve this problem by providing synthetic and real datasets for spatial join, source code for constructing more datasets, and several baseline solutions that researchers can further extend and compare to.
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DOI:
10.1145/3377000.3377005
发表时间:
2019
期刊:
SIGSPATIAL Special
影响因子:
--
作者:
Ghosh, Saheli;Vu, Tin;Eskandari, Mehrad Amin;Eldawy, Ahmed
通讯作者:
Eldawy, Ahmed
DOI:
--
发表时间:
2017
期刊:
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影响因子:
--
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通讯作者:
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DOI:
--
发表时间:
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期刊:
ACM SIGSPATIAL International Workshop on Advances in Geographic Information Systems
影响因子:
--
作者:
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通讯作者:
M. Mokbel
DOI:
--
发表时间:
2018
期刊:
影响因子:
--
作者:
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通讯作者:
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DOI:
10.1145/3474717.3484217
发表时间:
2021
期刊:
International Conference on Advances in Geographic Information Systems (SIGSPATIAL
影响因子:
--
作者:
Vu, Tin;Belussi, Alberto;Migliorini, Sara;Eldawy, Ahmed
通讯作者:
Eldawy, Ahmed